End of training

README.md

@@ -4,7 +4,7 @@ base_model: layoutlmv3
 tags:
 - generated_from_trainer
 datasets:
-- not-lain/sroie
+- mp-02/sroie
 metrics:
 - precision
 - recall
@@ -17,21 +17,21 @@ model-index:
       name: Token Classification
       type: token-classification
     dataset:
-      name: not-lain/sroie
-      type: not-lain/sroie
+      name: mp-02/sroie
+      type: mp-02/sroie
     metrics:
     - name: Precision
       type: precision
-      value: 0.9515865227347072
+      value: 0.9265995453069178
     - name: Recall
       type: recall
-      value: 0.9645225464190982
+      value: 0.9459549071618037
     - name: F1
       type: f1
-      value: 0.9580108677753993
+      value: 0.936177194421657
     - name: Accuracy
       type: accuracy
-      value: 0.9870755974971792
+      value: 0.9808185454918453
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -39,13 +39,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # layoutlmv3-finetuned-sroie
 
-This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the not-lain/sroie dataset.
+This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/sroie dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0596
-- Precision: 0.9516
-- Recall: 0.9645
-- F1: 0.9580
-- Accuracy: 0.9871
+- Loss: 0.0717
+- Precision: 0.9266
+- Recall: 0.9460
+- F1: 0.9362
+- Accuracy: 0.9808
 
 ## Model description
 
@@ -64,28 +64,24 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 10
-- eval_batch_size: 10
+- learning_rate: 1e-06
+- train_batch_size: 6
+- eval_batch_size: 6
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- training_steps: 1000
+- training_steps: 1500
 
 ### Training results
 
 | Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.5873  | 100  | 0.0548          | 0.9415    | 0.9453 | 0.9434 | 0.9830   |
-| No log        | 3.1746  | 200  | 0.0531          | 0.9377    | 0.9625 | 0.9499 | 0.9847   |
-| No log        | 4.7619  | 300  | 0.0550          | 0.9414    | 0.9595 | 0.9504 | 0.9851   |
-| No log        | 6.3492  | 400  | 0.0560          | 0.9500    | 0.9645 | 0.9572 | 0.9868   |
-| 0.0464        | 7.9365  | 500  | 0.0596          | 0.9516    | 0.9645 | 0.9580 | 0.9871   |
-| 0.0464        | 9.5238  | 600  | 0.0630          | 0.9502    | 0.9622 | 0.9562 | 0.9865   |
-| 0.0464        | 11.1111 | 700  | 0.0707          | 0.9489    | 0.9658 | 0.9573 | 0.9868   |
-| 0.0464        | 12.6984 | 800  | 0.0726          | 0.9515    | 0.9629 | 0.9572 | 0.9868   |
-| 0.0464        | 14.2857 | 900  | 0.0765          | 0.9510    | 0.9652 | 0.9580 | 0.9871   |
-| 0.0048        | 15.8730 | 1000 | 0.0773          | 0.9500    | 0.9645 | 0.9572 | 0.9868   |
+| No log        | 2.3810  | 250  | 0.1477          | 0.8827    | 0.8654 | 0.8739 | 0.9628   |
+| 0.3014        | 4.7619  | 500  | 0.0899          | 0.9138    | 0.9274 | 0.9205 | 0.9759   |
+| 0.3014        | 7.1429  | 750  | 0.0765          | 0.9257    | 0.9377 | 0.9316 | 0.9795   |
+| 0.0669        | 9.5238  | 1000 | 0.0717          | 0.9266    | 0.9460 | 0.9362 | 0.9808   |
+| 0.0669        | 11.9048 | 1250 | 0.0713          | 0.9216    | 0.9476 | 0.9344 | 0.9803   |
+| 0.0562        | 14.2857 | 1500 | 0.0712          | 0.9203    | 0.9493 | 0.9346 | 0.9803   |
 
 
 ### Framework versions

all_results.json

@@ -1,10 +1,10 @@
 {
-    "predict_accuracy": 0.9890338907358706,
-    "predict_f1": 0.9620923688131104,
-    "predict_loss": 0.06438335031270981,
-    "predict_precision": 0.9600264288074001,
-    "predict_recall": 0.9641672196416722,
-    "predict_runtime": 15.9404,
-    "predict_samples_per_second": 10.916,
-    "predict_steps_per_second": 1.129
+    "predict_accuracy": 0.9826824790353793,
+    "predict_f1": 0.9401396740937812,
+    "predict_loss": 0.06455250084400177,
+    "predict_precision": 0.9423333333333334,
+    "predict_recall": 0.9379562043795621,
+    "predict_runtime": 17.0658,
+    "predict_samples_per_second": 10.196,
+    "predict_steps_per_second": 1.699
 }

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:0bbeb4c53165eb39e3cb2824f100e5f0a60f33a6b04c8dacbc2358d116ea3cee
 size 501349380

predict_results.json

@@ -1,10 +1,10 @@
 {
-    "predict_accuracy": 0.9890338907358706,
-    "predict_f1": 0.9620923688131104,
-    "predict_loss": 0.06438335031270981,
-    "predict_precision": 0.9600264288074001,
-    "predict_recall": 0.9641672196416722,
-    "predict_runtime": 15.9404,
-    "predict_samples_per_second": 10.916,
-    "predict_steps_per_second": 1.129
+    "predict_accuracy": 0.9826824790353793,
+    "predict_f1": 0.9401396740937812,
+    "predict_loss": 0.06455250084400177,
+    "predict_precision": 0.9423333333333334,
+    "predict_recall": 0.9379562043795621,
+    "predict_runtime": 17.0658,
+    "predict_samples_per_second": 10.196,
+    "predict_steps_per_second": 1.699
 }

runs/Aug26_23-55-04_bernini/events.out.tfevents.1724710668.bernini.28246.1

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+size 560